Adaptive Fuzzy Backstepping Sliding Mode Control for a 3-DOF Hydraulic Manipulator with Nonlinear Disturbance Observer for Large Payload Variation

Neural Adaptive Dynamic Surface Asymptotic Tracking Control of Hydraulic Manipulators With Guaranteed Transient Performance

In this article, a novel neural network (NN)-based adaptive dynamic surface asymptotic tracking controller with guaranteed transient performance is proposed for n -degrees of freedom (DOF) hydraulic manipulators. To fulfill the work, the entire manipulator system model, including hydraulic actuator dynamics, is first established. Then, the neural adaptive dynamic surface controller is designed, in which the NN is utilized to approximate the unknown joint coupling dynamics, while the approximation error and uncertainties of the actuator dynamics are addressed by the nonlinear robust control law with adaptive gains. In addition, a modified funnel function that ensures the joint tracking errors remains within a predefined funnel boundary and is skillfully incorporated into the adaptive dynamic surface control (ADSC) design to achieve a guaranteed transient tracking performance. The theoretical analysis reveals that both the guaranteed transient tracking performance and asymptotic stability can be achieved with the proposed controller. Contrastive simulations are performed on a 2-DOF hydraulic manipulator to demonstrate the superiority of the proposed controller.

Active Disturbance Rejection Contouring Control of Robotic Excavators with Output Constraints and Sliding Mode Observer

This paper proposes an active disturbance rejection contouring control scheme for robotic excavators suffering from model uncertainties, external disturbances, and unmeasurable states. A sliding mode observer (SMO) is firstly designed to precisely estimate both joint velocities and lumped uncertainties and disturbances. These estimations are then fed back into the main controller which is constructed based on the task coordinate frame (TCF) approach. Furthermore, to meet the requirements of high-accuracy control performance, the barrier Lyapunov function (BLF) is utilized in the control design together with the previous techniques, which guarantees the stability of the whole system. Finally, numerical simulation is conducted with a high-reliability excavator model to verify the effectiveness of the proposed control algorithm under various operating conditions. In future work, further practical problems will be conducted to realize the application of robotic excavators in construction.

Research on Seawater Hydraulic Internal Ball Gear Pump

With high demands for novel technologies in the marine mechatronic instrumentality and the limitations of the present hydraulic pumps, a novel bidirectional seawater hydraulic internal ball gear pump is proposed to accomplish the function of fluid power transmission and control. The proposed hydraulic pump can be used for hydraulic buoyancy control systems of underwater vehicles and different marine mechatronic equipment. In this paper, the model, the meshing and the flow characteristics of the internal ball gear pump are developed. The radial unbalance force of the pump, leakage, and flow pulsation are also analyzed. The new type of eccentric shaft-hole rotary sealing designed in this paper can eliminate axial leakage and is expected to improve volumetric efficiency, working pressure, and power density. Simulation and experimental results show that: (1) by using the concave/convex ball gears rather than the existing gears, the concave ball gear drives the convex ball ring to rotate, realizing energy transfer and conversion; (2) compared with the water hydraulic internal gear pump, the internal ball gear pump has excellent performance. Experimental results also show that when the speed is 1500 rpm, the maximum operating pressure can reach 7 MPa. At 2 MPa, its volumetric efficiency and flow can reach 75% and 0.189L/min, respectively. The outcomes of this study show that the proposed seawater hydraulic internal ball gear pump is effective and has a lot of potential.

Research on hydraulic motor control system based on fuzzy neural network combing sliding mode control and time delay estimation

The precise motion control of a hydraulic motor system has some problems due to uncertain disturbance, complex nonlinear dynamics. Traditional methods are difficult to obtain the desired control performance. In this paper, a new fuzzy neural network (FNN) combined with terminal sling mode control (TSMC) and time delay estimation (TDE) is proposed. FNN is used to adjust the parameter of TSMC to reduce the time for the system to reach the equilibrium point and chatting. To increase the accuracy of the system, TDE is used to compensate the error caused by uncertain disturbance. This controller was simulated in Amesim and Simulink, and the results showed that the control scheme proposed in this paper has the smallest angular displacement error, angular velocity error and variance than other control schemes, such as PID and sliding mode control (SMC). Furthermore, the designed controller was implemented on a drill pipe automatic handling manipulator, and its control performance was verified.

Adaptive Robust Position Control of Electro-Hydraulic Servo Systems with Large Uncertainties and Disturbances

In this paper, a novel adaptive robust control (ARC) scheme is proposed for electro-hydraulic servo systems (EHSSs) with uncertainties and disturbances. All dynamic functions in system dynamics are effectively approximated by multi-layer radial basis function neural network (RBF NN)-based approximators with online adaptive mechanisms. Moreover, neural network-based disturbance observers (NN-DOBs) are established to actively estimate and efficiently compensate for the effects of not only the matched/mismatched but also the imperfections of RBF NN-based approximators on the control system. Based on that, the nonlinear robust control law which integrates RBF NNs and NN-DOBs is synthesized via the sliding mode control (SMC) approach to guarantee the high-accuracy position tracking performance of the overall control system. Furthermore, the problem of the combination between DOBs and RBF NNs is first introduced in this paper to treat both disturbances and uncertainties in the EHSS. The stability of the recommended control mechanism is proven by using Lyapunov theory. Finally, numerical simulations with several distinct frequency levels of reference trajectory are conducted to convincingly demonstrate the effectiveness of the proposed approach.

Modelling an Industrial Robot and Its Impact on Productivity

This research aims to design an efficient algorithm leading to an improvement of productivity by posing a multi-objective optimization, in which both the time consumed to carry out scheduled tasks and the associated costs of the autonomous industrial system are minimized. The algorithm proposed models the kinematics and dynamics of the industrial robot, provides collision-free trajectories, allows to constrain the energy consumed and meets the physical characteristics of the robot (i.e., restriction on torque, jerks and power in all driving motors). Additionally, the trajectory tracking accuracy is improved using an adaptive fuzzy sliding mode control (AFSMC), which allows compensating for parametric uncertainties, bounded external disturbances and constraint uncertainties. Therefore, the system stability and robustness are enhanced; thus, overcoming some of the limitations of the traditional proportional-integral-derivative (PID) controllers. The trade-offs among the economic issues related to the assembly line and the optimal time trajectory of the desired motion are analyzed using Pareto fronts. The technique is tested in different examples for a six-degrees-of-freedom (DOF) robot system. Results have proved how the use of this methodology enhances the performance and reliability of assembly lines.

Active Disturbance Rejection Control for Position Tracking of Electro-Hydraulic Servo Systems under Modeling Uncertainty and External Load

In this paper, an active disturbance rejection control is designed to improve the position tracking performance of an electro-hydraulic actuation system in the presence of parametric uncertainties, non-parametric uncertainties, and external disturbances as well. The disturbance observers (Dos) are proposed to estimate not only the matched lumped uncertainties but also mismatched disturbance. Without the velocity measurement, the unmeasurable angular velocity is robustly calculated based on the high-order Levant’s exact differentiator. These disturbances and angular velocity are integrated into the control design system based on the backstepping framework which guarantees high-accuracy tracking performance. The system stability analysis is analyzed by using the Lyapunov theory. Simulations based on an electro-hydraulic rotary actuator are conducted to verify the effectiveness of the proposed control method.

Safety Operation of n-DOF Serial Hydraulic Manipulator in Constrained Motion with Consideration of Contact-Loss Fault

In consideration of accidental contact-loss due to step-change or accidentally moving out of a constrained framework, this paper focuses on solving this problem during working processes of an n-degree-of-freedom hydraulic manipulator (n-DOF manipulator). In order to overcome this phenomenon, a fault detection methodology-based virtual energy tank is employed with a shaping function to prevent the end-effector from damage or unexpected motion. This technique helps to detect when the contact-loss happens by a virtual energy variable; thus, decoupling a force control regulation. Moreover, a new trajectory for smooth motion after contact-loss detection is also discussed to increase system robustness. Additionally, to enhance tracking performance, adaptive laws are designed to compensate for system uncertainties. Comparative simulations are given on the n-DOF hydraulic manipulator to evaluate effectiveness of the impedance-based energy tank methodology under the sudden step-changed environment. Moreover, influences of control gains and setup energy parameters to the system behaviors when contact-loss happens are remarkably discussed as indispensable criteria for further development. The simulated results certified the superior effectiveness and reliability of the suggested methodology over the conventional impedance control for safe operation.

Output Feedback Control via Linear Extended State Observer for an Uncertain Manipulator with Output Constraints and Input Dead-Zone

This paper proposes an output feedback controller with a linear extended state observer (LESO) for an n-degree-of-freedom (n-DOF) manipulator under the presence of external disturbance, an input dead-zone, and time-varying output constraints. First, these issues are derived in mathematical equations accompanying an n-DOF manipulator. The proposed control is designed based on the backstepping technique with the barrier Lyapunov function (BLF) and a LESO. The LESO is used for estimating both the unmeasured states and the lumped uncertainties including the unknown frictions, external disturbances, and input dead-zone, in order to enhance the accuracy of the robotic manipulator. Additionally, the BLF helps to avoid violation of the output constraints. The stability and the output constraint satisfaction of the controlled manipulator are theoretically analyzed and proven by the Lyapunov theorem with a barrier Lyapunov function. Some comparative simulations are carried out on a 3-DOF planar manipulator. The simulation results prove the significant performance improvement of the proposed control over the previous methods.